JP7263471B2 - Information processing device, information processing method and information processing program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

Conventionally, there has been known a technique in which a sender anonymously notifies a sender of a message. For example, storage means for storing list information that individually characterizes senders, reception control means for receiving messages from sender-side terminals together with identification information that specifies sender-side terminals, and transmission of messages from the identification information Sending a message anonymizing means for prohibiting association of the identification information received by the reception control means with the specific list information extracted from the storage means so as not to identify the person, and the message anonymized by the message anonymizing means. A message notification system is known that includes transmission control means for sending out to a destination terminal on the recipient side.

JP 2021-099742 A

However, the conventional technology described above cannot always support smooth communication. For example, in the above-described conventional technology, the sender simply sends a message anonymously to the other party. For this reason, for example, when the sender sends a message to the other party for the first time, or when the position of the sender and the other party is different, the psychology of the sender when sending a message to the other party hurdles are sometimes high. Therefore, the conventional technology described above has room for improvement in assisting smooth communication.

The present application has been made in view of the above, and proposes an information processing apparatus, an information processing method, and an information processing program capable of supporting smooth communication.

An information processing apparatus according to the present application includes a calculation unit that calculates a degree of familiarity indicating a degree of familiarity that a first person has with a second person, and first symbol information that symbolizes the first person. and the second symbol information indicating the characteristics of the second person symbolizing the second person so that the degree of similarity between the first characteristic information indicating the and a providing unit for providing the first person with the second symbol information after being changed by the changing unit.

According to one aspect of the embodiment, there is an effect that it is possible to support smooth communication.

FIG. 1 is a diagram for explaining an overview of information processing according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing apparatus according to the embodiment; 3 is a diagram illustrating an example of a user information storage unit according to the embodiment; FIG. 4 is a diagram illustrating an example of a history information storage unit according to the embodiment; FIG. FIG. 5 is a diagram illustrating an information processing procedure according to the embodiment; FIG. 6 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus.

Embodiments for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Also, in each of the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

(embodiment)
[1. Overview of information processing]
FIG. 1 is a diagram for explaining an overview of information processing according to an embodiment. The information processing shown in FIG. 1 is implemented by an information processing system 1 . The information processing system 1 is used by users of a SNS (Social Networking Service) service (hereinafter sometimes referred to as an anonymous SNS service) that allows a sender to anonymously send a message to a transmission partner. and an information processing device 100 that provides an anonymous SNS service. The terminal device 10 and the information processing device 100 are communicably connected by wire or wirelessly via a predetermined network N (not shown). The information processing system 1 shown in FIG. 1 may include any number of terminal devices 10 and any number of information processing apparatuses 100 .

The terminal device 10 is an information processing device used by users of the anonymous SNS service. The terminal device 10 is realized by, for example, a smart phone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. An application for using an anonymous SNS service is installed in the terminal device 10 .

Hereinafter, the user identified by the user ID "U1" may be referred to as "user U1". Thus, hereinafter, when "user U* (* is an arbitrary number)" is described, it indicates that the user is specified by the user ID "U*". For example, when "user U2" is described, the user is the user specified by the user ID "U2".

Also, hereinafter, the terminal device 10 will be described as the terminal devices 10-1 and 10-2 according to the user who uses the terminal device 10. FIG. For example, the terminal device 10-1 is the terminal device 10 used by the user U1. Also, for example, the terminal device 10-2 is the terminal device 10 used by the user U2. Further, hereinafter, the terminal devices 10-1 and 10-2 are referred to as the terminal device 10 when they are described without distinction.

The information processing device 100 is a server device that provides an anonymous SNS service. The information processing apparatus 100 also executes the information processing shown in FIG. In FIG. 1, the information processing device 100 receives a message for the user U2 from the terminal device 10-1 of the user U1 (step S1).

Subsequently, when receiving the message, the information processing apparatus 100 calculates a degree of familiarity indicating the degree of familiarity that the user U1 who sent the message has with the user U2 who is the transmission partner (step S2). For example, the information processing apparatus 100 inputs the number of times the user U1 has sent a message to the user U2 as an input value of the sigmoid function. Subsequently, the information processing apparatus 100 calculates the output value of the sigmoid function as the degree of familiarity that the user U1 has with the user U2.

Subsequently, after calculating the degree of familiarity, the information processing apparatus 100 uses a known morphing technique to generate first feature information indicating features of the image G1 including the face of the user U1 and an image including the face of the user U2. The image G2′ in the intermediate state is changed so that the degree of similarity with the second feature information indicating the feature of the image G2′ in the intermediate state obtained by synthesizing the image G2 and the image G1 becomes the degree of similarity based on the calculated degree of familiarity (step S3).

Subsequently, the information processing device 100 receives a reply message to the user U1 from the terminal device 10-2 of the user U2 (step S4). For example, the information processing apparatus 100 receives a message including character information T2 such as "To Mr. XX, how are you today?" from the terminal device 10-2.

Subsequently, when receiving the message, the information processing apparatus 100 provides the image G2' in the intermediate state after the change to the user U1 (step S5). For example, the information processing apparatus 100 generates the content C22 including the character information T2 included in the message received from the terminal apparatus 10-2 and the changed image G2' including the face of the user U2. Subsequently, the information processing device 100 transmits the generated content C22 to the terminal device 10-1 of the user U1.

As described above, the information processing apparatus 100 calculates the degree of familiarity indicating the degree of familiarity that the user U1 who has sent the message has with the user U2 who is the transmission partner. Further, the information processing apparatus 100 obtains first feature information indicating features of the image G1 including the face of the user U1, and features of an image G2′ in an intermediate state obtained by synthesizing the image G2 including the face of the user U2 and the image G1. The image G2' in the intermediate state is changed so that the degree of similarity with the second feature information indicating is the degree of similarity based on the degree of familiarity. Further, the information processing apparatus 100 provides the user U1 with the image G2' in the intermediate state after the change.

In this manner, the information processing apparatus 100 displays the image of the agent that mediates communication according to the degree of affinity that the user U1 who has sent the message has for the user U2 who is the transmission partner. , to an image including the face of the user U2 who is the transmission partner. That is, for example, when the user U1 has a low degree of familiarity with the user U2, the information processing apparatus 100 displays the image of the agent that mediates communication with the user U1 rather than the face of the user U2. By changing the image to include a face close to U2's face, it is possible to reduce the low sense of intimacy that user U1 has for user U2. As a result, the information processing apparatus 100 can reduce the low sense of intimacy that the user U1 has for the user U2, thereby making it easier for the user U1 to send a message to the user U2. can be done. Therefore, the information processing apparatus 100 can support smooth communication.

[2. Configuration example of information processing device]
Next, the configuration of the information processing apparatus 100 according to the embodiment will be described using FIG. FIG. 2 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 2, the information processing apparatus 100 has a communication section 110, a storage section 120, and a control section . Note that the information processing apparatus 100 may have an input unit (for example, a keyboard, a mouse, etc.) that receives various operations from the user of the information processing apparatus 100 or the like.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Also, the communication unit 110 is connected to a network N (not shown) by wire or wirelessly, and transmits and receives information to and from the terminal device 10, for example.

(storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 stores various programs (corresponding to an example of an information processing program). As shown in FIG. 2 , storage unit 120 has user information storage unit 121 and history information storage unit 122 .

(User information storage unit 121)
The user information storage unit 121 stores various information about users. 3 is a diagram illustrating an example of a user information storage unit according to the embodiment; FIG. In the example shown in FIG. 3, the user information storage unit 121 has items such as "user ID", "image data", and "audio data".

"User ID" indicates identification information for identifying a user. "Image data" indicates image data including the user's face. For example, "image data" indicates face image data of an icon of an anonymous SNS service registered by the user. Note that the “image data” may be image data including the user's face captured during a video call in the anonymous SNS service. "Voice data" indicates voice data including the user's voice. For example, "voice data" may be voice data including the user's voice recorded during a voice call in an anonymous SNS service.

Here, in the example shown in FIG. 3, abstract values such as "U1", "G1" and "V11" are used, but "U1", "G1" and "V11" are not specific values. It is assumed that information such as character strings and numerical values are stored.

(History information storage unit 122)
The history information storage unit 122 stores various kinds of information regarding the user's action history. 4 is a diagram illustrating an example of a history information storage unit according to the embodiment; FIG. In the example shown in FIG. 4, the history information storage unit 122 has items such as "user ID" and "transmission history".

"User ID" indicates identification information for identifying a user. The “transmission/reception history” indicates, for example, the transmission/reception history of messages of the user in the anonymous SNS service. The “transmission/reception history” may include the transmission/reception history of images in video calls and the transmission/reception history of voice data in voice calls in the anonymous SNS service.

Here, in the example shown in FIG. 4 , abstract values such as “U1” and “transmission/reception history #1” are used, but concrete values such as “U1” and “transmission/transmission history #1” are used. It is assumed that information such as columns and numerical values is stored.

(control unit 130)
Returning to the description of FIG. The control unit 130 is a controller. Various programs (corresponding to an example of an information processing program) stored in the internal storage device are executed by using a storage area such as a RAM as a work area.

As shown in FIG. 2, the control unit 130 has an acquisition unit 131, a calculation unit 132, a change unit 133, and a provision unit 134, and implements or executes the information processing operation described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 2, and may be another configuration as long as it performs the information processing described later.

(Acquisition unit 131)
The acquisition unit 131 acquires user information about the user from the terminal device 10 of the user. For example, the acquisition unit 131 acquires face image data of an icon of an anonymous SNS service registered by a user as an example of user information. Further, for example, the acquisition unit 131 may acquire image data including the user's face captured during a video call in an anonymous SNS service, as an example of user information. The acquisition unit 131 also acquires voice data including the user's voice as an example of user information. For example, the acquisition unit 131 may acquire, as an example of user information, voice data including the user's voice recorded during a voice call in an anonymous SNS service. Upon acquiring the user information, the acquisition unit 131 stores the acquired user information in the user information storage unit 121 in association with the user ID.

In addition, the acquisition unit 131 acquires history information regarding the action history of the user from the terminal device 10 of the user. For example, the acquisition unit 131 acquires a message transmission/reception history of a user in an anonymous SNS service as an example of history information. As an example of the history information, the acquisition unit 131 may acquire a transmission/reception history of images in a video call and a transmission/reception history of audio data in a voice call in an anonymous SNS service. Upon acquiring the history information, the acquisition unit 131 stores the acquired history information in the history information storage unit 122 in association with the user ID.

(Calculation unit 132)
The calculation unit 132 calculates a degree of familiarity that indicates the degree of familiarity that the first user has with the second user. Specifically, when receiving a message for the second user from the terminal device 10 of the first user, the calculation unit 132 refers to the history information storage unit 122 and determines that the first user Calculate the number of times the message has been sent to the second user. After calculating the number of times of transmission, the calculation unit 132 inputs the calculated number of times of transmission as an input value of the sigmoid function. Subsequently, the calculator 132 calculates the output value of the sigmoid function as the degree of familiarity that the first user has with the second user. In this way, the calculation unit 132 calculates a higher degree of familiarity as the number of transmissions of information from the first user to the second user increases.

(Change section 133)
The changing unit 133 determines that the degree of similarity between the first feature information indicating the features of the image including the face of the first user and the second feature information indicating the features of the image including the face of the second user is close. The image containing the face of the second user is changed so that the degree of similarity is based on the degree of similarity. Specifically, when the calculating unit 132 calculates the degree of familiarity, the changing unit 133 uses a known morphing technique to obtain first feature information indicating features of an image including the face of the first user, The degree of similarity between the image including the face of the second user and the second feature information indicating the features of the image in the intermediate state obtained by synthesizing the image including the face of the first user is the degree of similarity based on the calculated familiarity. The image in the intermediate state is changed so that

For example, the changing unit 133 inputs an image including the first user's face and an image including the second user's face to a machine learning model generated for morphing, and converts the first user's face The machine learning model outputs an image in an intermediate state obtained by synthesizing the image including the face of the second user and the image including the face of the second user. Subsequently, the changing unit 133 calculates the degree of similarity between the first feature information indicating the feature of the image including the face of the first user and the image in the intermediate state output from the machine learning model. Select intermediate state images that result in a degree of similarity based on proximity.

(Providing unit 134)
The providing unit 134 provides the image in the intermediate state after being changed by the changing unit 133 to the first user. For example, when the providing unit 134 receives a reply message to the first user from the second user's terminal device 10, the providing unit 134 receives the character information included in the reply message and the intermediate text after being changed by the changing unit 133. Generate content with state images. Subsequently, the providing unit 134 transmits the generated content to the terminal device 10 of the first user.

[3. Information processing procedure]
FIG. 5 is a diagram illustrating an information processing procedure according to the embodiment; As shown in FIG. 5, the calculation unit 132 of the information processing apparatus 100 calculates a degree of familiarity indicating the degree of familiarity that a first person has with a second person (step S101). For example, the calculator 132 calculates a higher degree of familiarity as the number of transmissions of information from the first person to the second person increases.

The changing unit 133 of the information processing apparatus 100 generates first feature information indicating a feature of first symbol information symbolizing a first person and second feature information indicating a feature of second symbol information symbolizing a second person. The second symbol information is changed so that the degree of similarity with is based on the degree of familiarity (step S102). For example, the changing unit 133 uses a known morphing technique to generate first feature information indicating features of an image including the face of the first person, an image including the face of the second person and the face of the first person. The image in the intermediate state is changed so that the degree of similarity with the second feature information indicating the feature of the image in the intermediate state obtained by synthesizing the image including is equal to the degree of similarity based on the calculated degree of familiarity.

The providing unit 134 of the information processing apparatus 100 provides the second symbol information after being changed to the first person (step S103). For example, the providing unit 134 provides the content including the image in the intermediate state after being changed by the changing unit 133 to the first person.

[4. Modification]
The information processing system 1 according to the above-described embodiments may be implemented in various different forms other than the above-described embodiments. Therefore, other embodiments of the information processing system 1 will be described below. In addition, the same code|symbol is attached|subjected to the same part as embodiment, and description is abbreviate|omitted.

[4-1. Another example of the first symbol information]
[4-1-1. Other examples of images]
In the above-described embodiment, the changing unit 133 generates the first feature information indicating the features of the image including the first user's face and the second feature information indicating the features of the image including the second user's face. A case has been described where the image including the face of the second user is changed so that the similarity of the first user is based on the familiarity. information other than an image containing the user's face.

Specifically, the first symbolic information may be an image containing the face of any person. For example, the acquisition unit 131 acquires an image including the face of an arbitrary person from the terminal device 10 of the first user instead of the image including the face of the first user. Next, when the calculating unit 132 calculates the degree of familiarity, the changing unit 133 uses a known morphing technique to generate first feature information indicating features of an image including the face of an arbitrary person and second usage information. The intermediate state is adjusted so that the similarity between the image including the face of the person and the second feature information indicating the features of the image in the intermediate state obtained by synthesizing the image including the face of an arbitrary person is the similarity based on the calculated degree of familiarity. change the image of In this way, the changing unit 133 determines that the degree of similarity between the first feature information indicating the features of the image including the face of an arbitrary person and the second feature information indicating the features of the image including the face of the second user is , the image including the face of the second user is changed so that the degree of similarity is based on the degree of familiarity.

Also, the first symbol information may be an image of a creature other than a person. For example, the acquisition unit 131 acquires an image of a creature other than a person from the terminal device 10 of the first user instead of the image including the face of the first user. Subsequently, when the calculating unit 132 calculates the degree of familiarity, the changing unit 133 uses a known morphing technique to obtain the first feature information indicating the features of the image of the creature other than the human and the image of the second user. The image in the intermediate state is changed so that the degree of similarity between the image including the face and the second feature information indicating the features of the image in the intermediate state obtained by synthesizing the image of the non-human creature is the degree of similarity based on the calculated degree of familiarity. Let In this way, the changing unit 133 determines that the degree of similarity between the first feature information indicating the features of the image of a living creature other than a human and the second feature information indicating the features of the image including the face of the second user is close. The image containing the face of the second user is changed so that the degree of similarity is based on the degree of similarity.

Also, the first symbol information may be an image of an object other than a living thing. For example, the acquiring unit 131 acquires an image of a non-living object (for example, an automobile) from the first user's terminal device 10 instead of the image including the first user's face. Next, when the calculating unit 132 calculates the degree of familiarity, the changing unit 133 uses a known morphing technique to obtain the first feature information indicating the features of the image of the non-living object and the second user's The image in the intermediate state is changed so that the degree of similarity between the image including the face and the image of the non-living object synthesized in the intermediate state and the second feature information indicating the characteristics of the image in the intermediate state is the degree of similarity based on the calculated degree of familiarity. Let In this way, the changing unit 133 determines that the degree of similarity between the first feature information indicating the feature of the image of the non-living object and the second feature information indicating the feature of the image including the face of the second user is close. The image containing the face of the second user is changed so that the degree of similarity is based on the degree of similarity.

In addition to the above, the acquisition unit 131 receives, from the first user's terminal device 10, an object image of an object other than a living thing (for example, a car), a biological image of a living thing other than a person, and the first image. Acquire three facial images containing the user's face. When the degree of familiarity calculated by the calculation unit 132 is less than the first threshold, the change unit 133 changes the first feature information indicating the characteristics of the object image, the image including the face of the second user, and the object image. The image in the intermediate state is changed so that the degree of similarity with the second feature information indicating the feature of the synthesized image in the intermediate state becomes the degree of similarity based on the calculated degree of familiarity.

Further, when the degree of familiarity calculated by the calculation unit 132 is equal to or more than the first threshold and less than the second threshold, the change unit 133 changes the first characteristic information indicating the characteristics of the biological image and the second user's face. The image in the intermediate state is changed so that the degree of similarity between the image containing and the second feature information indicating the features of the image in the intermediate state obtained by synthesizing the biological image becomes the degree of similarity based on the calculated degree of familiarity.

Further, when the degree of familiarity calculated by the calculation unit 132 is equal to or greater than the second threshold, the change unit 133 changes the first feature information indicating the features of the face image including the face of the first user and the second The degree of similarity between the image containing the user's face and the second feature information indicating the characteristics of the image in the intermediate state obtained by synthesizing the face image containing the first user's face is the degree of similarity based on the calculated familiarity. , the image in the intermediate state is changed.

Also, the first symbol information may be an animated picture of the face of the second user. The changing unit 133 converts first feature information indicating features of an animated image obtained by animating the face of the second user and second feature information indicating features of an image (actual image) including the face of the second user. The image including the face of the second user may be changed so that the degree of similarity with the second user is based on the degree of familiarity.

Note that the changing unit 133 determines that the degree of similarity between the first feature information indicating the features of the image including the face of the first user and the second feature information indicating the features of the image including the face of the second user is , the image including the second user's face may be changed for each part of the second user's face (parts such as eyes, nose, mouth, ears, etc.) so that the degree of similarity is based on the degree of familiarity. .

[4-1-2. voice data]
Further, in the above-described embodiment, the first symbol information symbolizing the first user (second symbol information symbolizing the second user) represents the face of the first user (second user). The first symbol information (second symbol information) may be information other than an image including the face of the first user (second user). Specifically, the first symbolic information that symbolizes the first user (the second symbolic information that symbolizes the second user) is the voice including the voice of the first user (second user). can be data.

For example, when the calculator 132 receives a voice message for the second user from the terminal device 10 of the first user, A degree of familiarity indicating the degree is calculated. When the calculating unit 132 calculates the degree of familiarity, the changing unit 133 uses a known voice morphing technique to convert first feature information indicating features of voice data including the voice of the first user and second feature information. The degree of similarity between the voice data including the voice of the user and the second characteristic information indicating the characteristics of the voice data in the intermediate state obtained by synthesizing the voice data including the voice of the first user is the degree of similarity based on the calculated familiarity. The audio data in the intermediate state is changed so that

In this way, the changing unit 133 generates the first feature information indicating the feature of the voice data including the voice of the first user and the second feature information indicating the feature of the voice data including the voice of the second user. The voice data including the voice of the second user is changed so that the similarity of is based on the degree of familiarity.

For example, the changing unit 133 inputs voice data including the voice of the first user and voice data including the voice of the second user to a machine learning model generated for voice morphing, and performs the first usage. The machine learning model outputs speech data in an intermediate state obtained by synthesizing the speech data including the voice of the second user and the speech data including the voice of the second user. Subsequently, the changing unit 133 determines that the degree of similarity with the first feature information indicating the feature of the voice data including the voice of the first user, out of the plurality of intermediate state voice data output from the machine learning model, is Intermediate speech data is selected so that the degree of similarity is based on the calculated degree of familiarity.

The providing unit 134 provides the first user with the voice data in the intermediate state after being changed by the changing unit 133 . For example, when receiving a reply voice message to the first user from the terminal device 10 of the second user, the providing unit 134 causes the changing unit 133 to change the language information included in the reply voice message. Contents to be reproduced are generated by audio data in an intermediate state after being processed. Subsequently, the providing unit 134 transmits the generated content to the terminal device 10 of the first user.

Note that the first symbolic information may be voice data including the voice of an arbitrary person. At this time, when the calculating unit 132 calculates the degree of familiarity, the changing unit 133 uses a known voice morphing technique to perform first feature information indicating a feature of voice data including the voice of an arbitrary person, The degree of similarity between the speech data including the voice of the first user and the second feature information indicating the features of the voice data in the intermediate state obtained by synthesizing the voice data including the voice of the first user is similarity based on the calculated familiarity Change the audio data in the intermediate state so that the In this way, the changing unit 133 determines the degree of similarity between the first feature information indicating the feature of the voice data including the voice of an arbitrary person and the second feature information indicating the feature of the voice data including the voice of the second person. changes voice data including the voice of the second person so that the degree of similarity is based on the degree of familiarity.

[4-2. Other methods for calculating degree of familiarity]
Further, in the above-described embodiment, a case has been described in which the calculation unit 132 calculates a higher degree of familiarity as the number of transmissions of information from the first user to the second user increases. The degree calculation method is not limited to this.

For example, the calculation unit 132 refers to the history information storage unit 122 and refers to a representative value (for example, average value, median value, , mode, etc.). Subsequently, after calculating the representative value of the response speed, the calculation unit 132 inputs the calculated representative value of the response speed as the input value of the sigmoid function. Subsequently, the calculator 132 calculates the output value of the sigmoid function as the degree of familiarity that the first user has with the second user. In this way, the calculation unit 132 may calculate the degree of familiarity to be higher as the response speed of the first user to the information received from the second user is faster.

The calculation unit 132 also refers to the history information storage unit 122 to acquire messages sent by the first user to the second user. Subsequently, when acquiring the message, the calculation unit 132 extracts words included in the acquired message using a known natural language processing technique. Subsequently, the calculation unit 132 calculates the number of words and phrases that match the words and phrases separately defined as words and phrases indicating familiarity with the other party from among the extracted words and phrases. Subsequently, after calculating the number of words and phrases indicating familiarity with the other party, the calculation unit 132 inputs the calculated number of words and phrases as the input value of the sigmoid function. Subsequently, the calculator 132 calculates the output value of the sigmoid function as the degree of familiarity that the first user has with the second user. In this way, the calculation unit 132 calculates a higher degree of familiarity as the language information transmitted by the first user to the second user contains more words and phrases indicating familiarity with the other user. good. Note that the calculation unit 132 may refer to the history information storage unit 122 to acquire the voice message sent by the first user to the second user. When the voice message is acquired, the calculator 132 may convert the linguistic information included in the voice message into characters using a known voice recognition technology, and then perform the above-described natural language processing.

The calculation unit 132 also refers to the history information storage unit 122 to refer to the image data transmitted by the first user to the second user (for example, the first usage data recorded during the video call). image data including the person's face). Upon obtaining the image data, the calculation unit 132 estimates the facial expression of the first user using a known image analysis technique. Subsequently, when estimating the facial expression of the first user, the calculation unit 132 calculates the number of appearances of the facial expression that matches the facial expression that is separately defined as a facial expression that indicates familiarity with the other person (for example, a facial expression that indicates joy). calculate. Subsequently, after calculating the number of appearances of the facial expression indicating familiarity with the other party, the calculation unit 132 inputs the calculated number of appearances as the input value of the sigmoid function. Subsequently, the calculator 132 calculates the output value of the sigmoid function as the degree of familiarity that the first user has with the second user. In this way, the calculation unit 132 determines that the image including the face of the first user transmitted by the first user to the second user contains more facial expressions indicating familiarity with the other user. , the degree of closeness may be calculated to be high.

[4-3. Application to other services]
In the above-described embodiment, the information processing by the information processing apparatus 100 is applied to an SNS service that allows senders to anonymously send messages, but the present invention is not limited to this. For example, the information processing by the information processing apparatus 100 described above may be applied to SNS services whose senders are not anonymous, message services such as mail services, and video conference systems.

[5. effect〕
As described above, the information processing apparatus 100 according to the embodiment includes the calculation unit 132, the change unit 133, and the provision unit . The calculation unit 132 calculates a degree of familiarity that indicates the degree of familiarity that the first person has with the second person. The changing unit 133 determines that the degree of similarity between the first feature information indicating the feature of the first symbol information symbolizing the first person and the second feature information indicating the feature of the second symbol information symbolizing the second person is , the second symbol information is changed so that the degree of similarity is based on the degree of familiarity. The providing unit 134 provides the second symbol information changed by the changing unit 133 to the first person.

In this way, the information processing apparatus 100 stores the information of the agent mediating the communication with the first symbol symbolizing the first person according to the degree of familiarity that the first person has with the second person. The information is changed step by step to the second symbolic information that symbolizes the second person. That is, for example, when the degree of affinity that the first person has for the second person is low, the information processing apparatus 100 sets the information of the agent mediating communication to the first symbol information rather than the second symbol information. By changing the information closer to the symbolic information, it is possible to reduce the low sense of affinity that the first person has for the second person. As a result, the information processing apparatus 100 can reduce the low sense of intimacy that the first person has for the second person. can be made easier to send. Therefore, the information processing apparatus 100 can support smooth communication.

Also, the first symbol information is an image of a creature other than a person, the second symbol information is an image including the face of a second person, and the changing portion 133 indicates the characteristics of the image of the creature other than a person. The image including the face of the second person is changed so that the degree of similarity between the first feature information and the second feature information indicating the features of the image including the face of the second person is based on the degree of familiarity. Let

As a result, for example, when the degree of familiarity that the first person has for the second person is low, the information processing apparatus 100 displays the image of the agent mediating the communication rather than the face of the second person. By changing the image to an image that is close to the living creature that the first person likes, it is possible to reduce the low sense of affinity that the first person has for the second person.

Further, the first symbol information is an image including the face of an arbitrary person, the second symbol information is an image including the face of a second person, and the changing unit 133 is an image including the face of an arbitrary person. and the second feature information indicating the features of the image including the face of the second person is the similarity based on the degree of familiarity. Vary the containing image.

As a result, for example, when the degree of familiarity that the first person has for the second person is low, the information processing apparatus 100 displays the image of the agent mediating the communication rather than the face of the second person. By changing the image to an image close to the face of any person that the first person likes, it is possible to reduce the low sense of familiarity that the first person has for the second person.

Also, the arbitrary person is the first person, and the changing unit 133 converts the first feature information indicating the features of the image including the face of the first person and the features of the image including the face of the second person. The image including the face of the second person is changed so that the degree of similarity with the indicated second feature information becomes the degree of similarity based on the degree of familiarity.

As a result, for example, when the degree of familiarity that the first person has for the second person is low, the information processing apparatus 100 displays the image of the agent mediating the communication rather than the face of the second person. By changing the first person's face to an image close to the first person's face, the first person's low sense of closeness to the second person can be reduced.

Further, the first symbol information is voice data including the voice of an arbitrary person, the second symbol information is voice data including the voice of a second person, and the changing unit 133 converts the voice of the arbitrary person. The second feature information is set so that the similarity between the first feature information indicating the feature of the voice data including the voice of the second person and the second feature information indicating the feature of the voice data including the voice of the second person is similarity based on the degree of familiarity. To change voice data including human voice.

As a result, for example, when the degree of affinity that the first person has for the second person is low, the information processing apparatus 100 replaces the voice data of the agent mediating communication with the voice of the second person. By changing the voice data to voice data closer to the voice of any person preferred by the first person than the first person, it is possible to reduce the low sense of intimacy that the first person has for the second person.

Also, the arbitrary person is the first person, and the changing unit 133 converts the first feature information indicating the feature of the voice data including the voice of the first person and the voice data including the voice of the second person. The voice data including the voice of the second person is changed so that the degree of similarity with the second feature information indicating the feature becomes the degree of similarity based on the degree of familiarity.

As a result, for example, when the degree of affinity that the first person has for the second person is low, the information processing apparatus 100 replaces the voice data of the agent mediating communication with the voice of the second person. By changing the voice data closer to the first voice than the first voice, it is possible to reduce the low sense of intimacy that the first person has for the second person.

Further, the calculation unit 132 calculates a higher degree of familiarity as the number of transmissions of information from the first person to the second person increases.

Accordingly, the information processing apparatus 100 can appropriately calculate the degree of familiarity based on the number of transmissions of information from the first person to the second person.

Further, the calculation unit 132 calculates a higher degree of familiarity as the response speed of the first person to the information received from the second person is faster.

Accordingly, the information processing apparatus 100 can appropriately calculate the degree of familiarity based on the speed of the response of the first person to the information received from the second person.

In addition, the calculation unit 132 calculates a higher degree of familiarity as the linguistic information transmitted by the first person to the second person includes more words and phrases indicating familiarity with the other person.

Accordingly, the information processing apparatus 100 can appropriately calculate the degree of familiarity based on the number of words and phrases indicating familiarity included in the linguistic information transmitted by the first person to the second person. .

In addition, the calculation unit 132 increases the degree of familiarity as the image including the face of the first person transmitted by the first person to the second person includes more facial expressions indicating familiarity with the other person. calculate.

As a result, the information processing apparatus 100 can determine the appropriate facial expression based on the number of facial expressions indicating familiarity with the other party included in the image including the face of the first person that the first person has transmitted to the second person. can be calculated.

[6. Hardware configuration]
Also, the information processing apparatus 100 according to the above-described embodiments is implemented by a computer 1000 configured as shown in FIG. 6, for example. FIG. 6 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus 100. As shown in FIG. Computer 1000 includes CPU 1100 , RAM 1200 , ROM 1300 , HDD 1400 , communication interface (I/F) 1500 , input/output interface (I/F) 1600 and media interface (I/F) 1700 .

The CPU 1100 operates based on programs stored in the ROM 1300 or HDD 1400 and controls each section. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. Communication interface 1500 receives data from another device via a predetermined communication network, sends the data to CPU 1100, and transmits data generated by CPU 1100 to another device via a predetermined communication network.

The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, through an input/output interface 1600 . CPU 1100 acquires data from an input device via input/output interface 1600 . CPU 1100 also outputs the generated data to an output device via input/output interface 1600 .

Media interface 1700 reads programs or data stored in recording medium 1800 and provides them to CPU 1100 via RAM 1200 . CPU 1100 loads such a program from recording medium 1800 onto RAM 1200 via media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. etc.

For example, when the computer 1000 functions as the information processing apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the functions of the control unit 130 by executing programs loaded on the RAM 1200 . CPU 1100 of computer 1000 reads these programs from recording medium 1800 and executes them, but as another example, these programs may be obtained from another device via a predetermined communication network.

As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to carry out the invention in other forms with modifications.

[7. others〕
Further, among the processes described in the above embodiments and modifications, all or part of the processes described as being performed automatically can be performed manually, or described as being performed manually. All or part of the processing can also be performed automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

For example, in the above-described embodiment, an example in which the information processing system 1 is a central processing type (also referred to as a centralized type) computing system has been described, but the configuration of the information processing system 1 is not limited to this. For example, the information processing system 1 may be a distributed computing system configured with a plurality of terminal devices 10 . In this case, in the information processing system, a plurality of terminal devices 10 are connected to each other via a network. Further, in this case, in the information processing system, the functions of the information processing device 100 described with reference to FIG. 2 are implemented in each terminal device 10 .

The information processing apparatus 100 described above may be implemented by a plurality of server computers, and depending on the function, may be implemented by calling an external platform or the like using an API (Application Programming Interface), network computing, or the like. can be changed flexibly.

Also, the above-described embodiments and modifications can be appropriately combined within a range that does not contradict the processing content.

Also, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the calculation unit can be read as calculation means or a calculation circuit.

1 information processing system 10 terminal device 100 information processing device 110 communication unit 120 storage unit 121 user information storage unit 122 history information storage unit 130 control unit 131 acquisition unit 132 calculation unit 133 change unit 134 provision unit

Claims (12)

a calculation unit that calculates a degree of familiarity indicating the degree of familiarity that a first person has with a second person;
The degree of similarity between the first feature information indicating the feature of the first symbol information symbolizing the first person and the second feature information indicating the feature of the second symbol information symbolizing the second person a changing unit that changes the second symbolic information so as to obtain a degree of similarity based on the degree of similarity;
a providing unit that provides the first person with the second symbol information changed by the changing unit;
Information processing device. the first symbolic information is an image of a creature other than a human,
the second symbolic information is an image including the face of the second person;
The changing part is
The degree of similarity between the first feature information indicating the features of the image of the creature other than the human and the second feature information indicating the features of the image including the face of the second person is the degree of similarity based on the degree of familiarity. changing the image containing the face of the second person so that
The information processing device according to claim 1 . the first symbolic information is an image containing the face of an arbitrary person;
the second symbolic information is an image including the face of the second person;
The changing part is
The degree of similarity between the first feature information indicating features of the image including the face of the arbitrary person and the second feature information indicating features of the image including the face of the second person is based on the degree of familiarity. changing the image containing the face of the second person so as to achieve similarity;
The information processing apparatus according to claim 1 or 2. The arbitrary person is the first person,
The changing part is
The degree of similarity between the first feature information indicating the features of the image including the face of the first person and the second feature information indicating the features of the image including the face of the second person is the degree of familiarity. changing the image containing the face of the second person so that the similarity is based on
The information processing apparatus according to claim 3. the first symbolic information is voice data including voice of an arbitrary person;
the second symbolic information is voice data including voice of the second person;
The changing part is
The degree of similarity between the first feature information indicating the feature of the voice data including the voice of the arbitrary person and the second feature information indicating the feature of the voice data including the voice of the second person is the degree of familiarity. changing the audio data including the voice of the second person so that the similarity is based on
The information processing apparatus according to any one of claims 1 to 4. The arbitrary person is the first person,
The changing part is
The degree of similarity between the first feature information indicating the feature of the voice data including the voice of the first person and the second feature information indicating the feature of the voice data including the voice of the second person is the degree of familiarity. changing the voice data including the voice of the second person so that the degree of similarity is based on the degree of similarity;
The information processing device according to claim 5 . The calculation unit
The higher the number of times the first person has sent information to the second person, the higher the degree of familiarity is calculated.
The information processing apparatus according to any one of claims 1 to 6. The calculation unit
The faster the response speed of the first person to the information received from the second person, the higher the degree of familiarity is calculated.
The information processing apparatus according to any one of claims 1 to 7. The calculation unit
The closer the linguistic information transmitted by the first person to the second person, the more words and phrases indicating familiarity with the other person are included, the higher the degree of familiarity is calculated;
The information processing apparatus according to any one of claims 1 to 8. The calculation unit
The closer the image containing the face of the first person sent by the first person to the second person, the more facial expressions indicating familiarity with the other person are included, the higher the degree of familiarity is calculated.
The information processing apparatus according to any one of claims 1 to 9. A computer-executed information processing method comprising:
a calculation step of calculating a degree of affinity indicating the degree of affinity that the first person has for the second person;
The degree of similarity between the first feature information indicating the feature of the first symbol information symbolizing the first person and the second feature information indicating the feature of the second symbol information symbolizing the second person a changing step of changing the second symbolic information so as to obtain a degree of similarity based on
a providing step of providing the second symbol information changed by the changing step to the first person;
Information processing method including. a calculation procedure for calculating a degree of affinity indicating the degree of affinity that a first person has for a second person;
The degree of similarity between the first feature information indicating the feature of the first symbol information symbolizing the first person and the second feature information indicating the feature of the second symbol information symbolizing the second person a changing procedure for changing the second symbolic information so as to obtain a degree of similarity based on the similarity;
a providing procedure for providing the first person with the second symbol information after being changed by the changing procedure;
An information processing program that causes a computer to execute

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